An implantable medical apparatus which executes cardiovascular control operations may evaluate cardiac electrical signals for many purposes. A cardiac control instrument analyzes cardiac signals to determine how well the cardiovascular system is performing. As a result of this analysis, the instrument responds to the detection of a predetermined criteria by automatically initiating control operations. One class of signal analyzers examines the time sequence of cardiac signal amplitudes to detect changes in the morphology, or shape, of the cardiac waveform which are indicative of cardiac function.
Most common cardiac control devices, including cardiac pacemakers, employ a rudimentary form of signal morphology analysis. These devices sense the amplitude of intracardiac electrogram signals and compare the instantaneous sensed amplitude to a preset threshold value. If the signal amplitude is larger than the threshold, the pacemaker inhibits its pacing stimulus generation response. Noise, including cardiac signals arising from sources other than those intended for measurement, adversely influences this simple control mechanism.
More sophisticated morphology analysis techniques are required for controlling other, more complex, diagnostic and therapeutic operations. One example of a function requiring a sophisticated analysis technique is the reliable detection of cardiac arrhythmias. The difficult problem of cardiac arrhythmia detection, including detection of ventricular tachycardia and fibrillation, has been addressed using many cardiac signal morphology procedures. One effective procedure, as proven in tests involving both intracardiac signal and surface electrocardiograms and reported by D. Lin et al. in "Identification of Ventricular Tachycardia Using Intracavitary Ventricular Electrograms: Analysis of Time and Frequency Domain Patterns", PACE, Vol. 11, pages 1592-1606 (1988), is the correlation of the detected signal with a previously recorded signal waveform which is known to characterize a particular diagnostic condition. Correlation is the summation of the products of point-by-point multiplications of two waveform sequences for the purpose of deriving a standard of similarity between the two waveform sequences. Unfortunately, correlation analysis requires such computational complexity that it is impractical in an implanted device. Because the device expends energy on each computational step and correlation requires so many computations, the lifetime of an implanted device performing correlation would be unreasonably short or the battery size too large for practical usage.
In many cardiac arrhythmia patients, there is a critical need for a reliable method for differentiating sinus rhythm from ventricular tachycardia (VT). If a cardiac control device had the capability of distinguishing sinus rhythm from VT, it could monitor heart activity to determine whether there was a need to perform a procedure for terminating heart disorders or arrhythmias. (This procedure is called cardioversion). Most early methods for differentiating sinus rhythm from VT were based on analyzing the timing between consecutive R-waves within a sensed electrocardiogram. Diagnostic devices would determine the R-wave rate and compare it to a predetermined maximum rate of sinus tachycardia. Some devices would also analyze the rate stability of the heart and the quickness of the onset of rate changes. Because these rate change characteristics of the R-wave always accompany ventricular tachycardias, a device controlled by these procedures will consistently detect and respond to such arrhythmias. Unfortunately, a normally functioning heart also may exhibit these rate change characteristics. For example, such rate changes may indicate only that the patient is exercising. Therefore, in addition to monitoring the rate, it is beneficial for a device to analyze the morphology of cardiac signals.
Langer et al., in U.S. Pat. No. 4,202,340, entitled "Method and Apparatus for Monitoring Heart Activity, Detecting Abnormalities, and Cardioverting a Malfunctioning Heart", issued May 13, 1980, describe an antitachycardia pacing system which detects arrhythmias by analyzing the morphology of cardiac signals. The arrhythmia detection system of the Langer et al. invention analyzes cardiac signal morphology statistically by developing a probability density function, which compares the amplitudes and locations of points in an analyzed cardiac waveform with the expected locations of points of a predetermined "normal" waveform. When the waveform becomes irregular, as measured by the probability density function, this indicates an abnormal cardiac function. The probability density function defines the fraction of time, on the average, that a signal spends between two amplitude limits. The basis for decision in this process is that the amount of time spent at baseline in each cardiac cycle is significantly longer during sinus rhythm than during ventricular tachycardia or ventricular fibrillation. The probability density function is the measure of time the signal spends away from the isoelectric baseline. It is markedly different during ventricular fibrillation than it is during normal sinus rhythm. The probability density function detects ventricular fibrillation (VF) reliably since the signal is seldom near the isoelectric line during VF. However, the probability density function is not nearly as reliable for detecting ventricular tachycardia.
The probability density function approach to arrhythmia detection is often unreliable because, if the predetermined "normal" waveform is not properly synchronized with the analyzed waveform, the device may incorrectly classify a waveform as a fibrillation condition upon the occurrence of some forms of high rate, or even low rate, ventricular tachycardia, in addition to true ventricular fibrillation. A particular problem occurs in the presence of ventricular conduction abnormalities. Defibrillation which is triggered by a high rate tachycardia is acceptable because high rate tachycardia can be fatal if it occurs at an elevated rate so considerable that not enough blood is pumped to sustain the body. However, generating defibrillation pulses in the event of low rate, non-life threatening tachycardia is inappropriate and possibly harmful.
Correlation analysis of intra-cavitary ventricular electrograms is another technique for analyzing cardiac waveform morphology which improves specificity of arrhythmia recognition. Correlation waveform analysis is a reliable technique for discriminating ventricular tachycardia from sinus rhythm. It has been used for over two decades in the analysis of surface lead morphology as well as for analyzing esophageal electrograms, intra-ventricular electrograms and intra-atrial electrograms. While correlation analysis is effective, it requires a waveform sampling rate of about 1 kHz to properly distinguish arrhythmia waveforms. Furthermore, the number of computations it requires is too demanding for usage in the low energy environment of an implantable device.
One modified technique for performing standard correlation is by multiplying the waveform sequences in a section-by section manner called piecewise correlation analysis, which provides for a reduction in the number of required computations by limiting the correlation procedure to operate only in the vicinity of the R-wave. In one example of piecewise correlation, a signal processing system defines a representative "normal" signal by measuring a ventricular electrogram signal template when the heart is functioning with a normal sinus rhythm. The system specifies this template by "windowing" the waveform, detecting the QRS complex of the cardiac signal and storing a predetermined number of samples before and after the QRS complex. For example, a waveform window may include 64 samples, which contain the QRS complex and are acquired at a 1000 Hz rate. The system averages a number of these waveform window for a preset number of cardiac cycles with the QRS complex for each cardiac cycle occurring at the same sample location within the window. After sampling and storing the template waveform, the system samples the ventricular electrogram at the same rate and for the same number of samples as was done when acquiring the template samples. The device correlates these samples with the average sinus rhythm template on a beat-by-beat basis.
To provide accurate detection of ventricular tachycardia, the piecewise correlation technique requires that the QRS complexes of the template and the sample electrogram are aligned. In piecewise correlation analysis, accurate template alignment is very important to successfully distinguish ventricular tachycardia from normal sinus rhythm or atrial fibrillation. In practice, alignment errors greater than four to five milliseconds cause a large and unpredictable variability in correlator results. Furthermore, alignment errors frequently are not recognized since a sensing determination aligned on some feature other than the R-wave may still result in a high correlation output.
Reliable template alignment is not a simple procedure. For example, a system which aligns R-waves according to a measured point of maximum intracardiac electrogram (IEGM) amplitude or corresponding to the peak derivative of the signal does not provide adequate alignment due to the large variability in amplitude and slope of the signal waveform. Signal processing of the cardiac signal to clarify the position of the R-wave using a variety of search windows and filtering techniques is helpful for particular signal morphologies but no single alignment procedure is adequate for all patients. The wide variability in cardiac signal morphologies for different patients and also for different times for the same patient cause these alignment difficulties.
Furthermore, a system which performs window alignment based on the peak cardiac signal amplitude is susceptible to errors from T-wave sensing. Occasional patients may display T-waves which are consistently larger in amplitude than R-waves. Consequently, windows may align on the T-wave or may align on the R- and T-waves in alternating cardiac cycles. Systems which align the template and sample signals based on the location of the sensed peak derivative commonly err from five to ten milliseconds because of the noisy nature of derivative signals. When combined with low pass filtering, alignment by peak derivative sensing improves somewhat but remains unacceptable.
The small size of the piecewise correlation window which is necessary to provide the computational efficiency for an implantable device leads to an additional source of alignment error. As the device performs piecewise correlation over a single cardiac cycle it may detect multiple peaks, possibly caused by T-wave sensing or detection of multiple peaks associated with the R-wave.
Full scanning correlation, in which a continuously sampled cardiac signal is correlated with a template sequence having a predetermined length smaller than the duration of the shortest possible cardiac cycle, avoids the alignment problems inherent in piecewise correlation. Unfortunately, full scanning correlation requires an excessive number of computations, and therefore too much power drain, for an implantable device.
It is, therefore, a primary object of the present invention to provide for processing of cardiac electrical signal data in a compressed form, thereby reducing the computational and energy requirements of the apparatus.
It is a further object of the present invention to provide a low power demand device and a reliable detection circuit to accurately identify ventricular tachycardia and ventricular fibrillation.
It is an additional object of the present invention to provide a system for reliably detecting abnormal ventricular signals, based on the morphology of such signals, in which the system does not require alignment of a predetermined template signal and the cardiac electrical signal under examination.
It is a still further object of the present invention to provide a system for reducing the data storage and transmission requirements of a diagnostic test device.
Further objects and advantages of this invention will become apparent as the following description proceeds.